Unrolled-DOT: an interpretable deep network for diffuse optical tomography.

ABSTRACT:

Significance

Imaging through scattering media is critical in many biomedical imaging applications, such as breast tumor detection and functional neuroimaging. Time-of-flight diffuse optical tomography (ToF-DOT) is one of the most promising methods for high-resolution imaging through scattering media. ToF-DOT and many traditional DOT methods require an image reconstruction algorithm. Unfortunately, this algorithm often requires long computational runtimes and may produce lower quality reconstructions in the presence of model mismatch or improper hyperparameter tuning.

Aim

We used a data-driven unrolled network as our ToF-DOT inverse solver. The unrolled network is faster than traditional inverse solvers and achieves higher reconstruction quality by accounting for model mismat

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC9995139 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature